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  5. Hybrid Energy Solution to Improve Irrigation Systems: HY4RES vs. HOMER Optimization Models

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Article
English
2024

Hybrid Energy Solution to Improve Irrigation Systems: HY4RES vs. HOMER Optimization Models

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0 Files

English
2024
Energies
Vol 17 (16)
DOI: 10.3390/en17164037

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Oscar Coronado-hernández
Oscar Coronado-hernández

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João Coelho
Afonso Alves
Jorge García Morillo
+3 more

Abstract

A new methodology for hybrid energy systems (HESs) was developed, namely the HY4RES model, tailored for the water sector, covering hybrid energy objective functions and grid or battery support using optimization algorithms in Solver, MATLAB, and Python, with evolutionary methods. HOMER is used for hybrid microgrids and allows for comparison with HY4RES, the newly developed model. Both models demonstrated flexibility in optimizing hybrid renewable solutions. This study analyzed an irrigation system for 3000 m3/ha (without renewables (Base case) and the Proposed system—with PV solar and pumped-hydropower storage to maximize cash flow over 25 years). Case 1—3000 m3/ha presented benefits due to PV supplying ~87% of energy, reducing grid dependency to ~13%. Pumped-hydropower storage (PHS) charges with excess solar energy, ensuring 24 h irrigation. Sensitivity analyses for Case 2—1000—and Case 3—6000 m3/ha—highlighted the advantages and limitations of water-energy management and system optimization. Case 2 was the most economical due to lower water-energy needs with noteworthy energy sales (~73.4%) and no need for the grid. Case 3 led to increased operating costs relying heavily on grid energy (61%), with PV providing only 39%. PHS significantly lowered operating costs and enhanced system flexibility by selling excess energy to the grid.

How to cite this publication

João Coelho, Afonso Alves, Jorge García Morillo, Oscar Coronado-hernández, Modesto Pérez‐Sánchez, Helena M. Ramos (2024). Hybrid Energy Solution to Improve Irrigation Systems: HY4RES vs. HOMER Optimization Models. Energies, 17(16), pp. 4037-4037, DOI: 10.3390/en17164037.

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Publication Details

Type

Article

Year

2024

Authors

6

Datasets

0

Total Files

0

Language

English

Journal

Energies

DOI

10.3390/en17164037

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